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Updated: Jun 13, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
A Multi-Locus and Machine Learning-Based Assessment of SNCA Variants in Alzheimer's Disease
Hatice Segmen1, Mustafa Yildiz2
1Department of Neurology, Kanuni Sultan Suleyman Training and Research Hospital, Saglik Bilimleri University, 34303 Istanbul, Türkiye.
This study explored single nucleotide polymorphisms (SNPs) in the SNCA gene and their link to Alzheimer's disease (AD). Some SNCA variants showed exploratory associations with AD risk, but clinical factors were stronger predictors.
Area of Science:
- Genetics and Neurology
- Neurodegenerative Diseases Research
Background:
- Alzheimer's disease (AD) is a complex neurodegenerative disorder with a significant genetic component.
- The SNCA gene, encoding alpha-synuclein, is implicated in neurodegenerative processes and has been investigated for its role in AD pathogenesis.
Purpose of the Study:
- To investigate the association between single nucleotide polymorphisms (SNPs) in the SNCA gene and Alzheimer's disease risk.
- To explore the potential of SNCA variants as predictors of AD and cognitive severity.
Main Methods:
- A case-control study involving 95 AD patients and 97 healthy controls.
- Analysis of four SNCA polymorphisms (rs2583988, rs2619363, rs2619364, rs10005233) using logistic regression, haplotype analysis, and Random Forest modeling.
- Multivariate logistic regression and ordinal logistic regression were employed to assess independent associations and cognitive severity.
Main Results:
- Significant exploratory associations were found for SNCA polymorphisms rs2583988, rs2619364, and rs2619363 with AD risk.
- Specific multi-locus genotype combinations showed links to increased disease risk.
- Clinical parameters, not SNCA variants, were independently associated with AD; education showed a protective effect against cognitive decline.
Conclusions:
- Selected SNCA variants demonstrated exploratory associations with AD in the studied cohort.
- These variants did not maintain validity as independent predictors in multivariate analyses.
- Further independent replication, correction for multiple testing, and functional validation are necessary before clinical application.
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